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LW1949 (version 1.1.0)

An Automated Approach to Evaluating Dose-Effect Experiments Following Litchfield and Wilcoxon (1949)

Description

The manual approach of Litchfield and Wilcoxon (1949) for evaluating dose-effect experiments is automated so that the computer can do the work.

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Version

Install

install.packages('LW1949')

Monthly Downloads

120

Version

1.1.0

License

GPL

Issues

0

Pull Requests

0

Stars

3

Forks

0

Maintainer

given=Jean V. family=Adams

Last Published

March 20th, 2017

Functions in LW1949 (1.1.0)

assessfit

Assess Fit of Dose-Response Curve
fitprobit

Fit a Probit Regression to Dose-Effect Data
fitlinear

Determine Linear Regression Coefficients from Dose-Effect Data
LW1949

Automated Litchfield and Wilcoxon (1949) Evaluation of Dose-Effect
LWP

User Friendly Evaluation of Dose-Effect Experiments using Litchfield-Wilcoxon
prettylog

Pretty Breakpoints on Log Scale
dataprep

Prepare Data
invprobit

Convert Probit Scale to Proportions
keeponly

Eliminate Consecutive Extreme Values
correctval

Predict the Corrected Proportional Effect
LWchi2

Chi-Squared Statistic
fitLWauto

Best Fit Using Litchfield and Wilcoxon Evaluation of Dose-Effect Experiments
LWestimate

Generate Litchfield and Wilcoxon Estimates
relPotency

Relative Potency of Two Toxins
fitHand

Best Fit Using Estimated Expected Effects
probit

Convert Proportions to the Probit Scale
predLinesLP

Add Litchfield and Wilcoxon Predictions to a Plot
fxcat

Define Effect Category
gamtable1

Fit a smooth GAM to Table 1 of Litchfield and Wilcoxon (1949)
plotDELP

Plot Dose-Effect Experiments
predLines

Add Litchfield and Wilcoxon Predictions to a Plot
coefprobit

Calculate the Coefficients of a Probit Regression Fit
estimable

Determine if a Dose-Effect Relation is Estimable
constrain

Constrain Data to a Specified Range
nomoCoord

Find the Coordinate from the Scale of a Nomograph
predlinear

Determine the Effective Dose from a Linear Regression Fit
predprobit

Determine the Effective Dose from a Probit Regression Fit
fill

Fill in Missing Values